Capability · AI Evals & Safety
Safety infrastructure, eval harnesses, and end-to-end tracing for production AI - built on golden datasets and QA loops that graduate from human review to recursive automation.
Trusted by 100+ founders
AI systems shipped with evals and tracing built in
Model and prompt changes gated by an eval run
Silent failures - every output traced and replayable
The Maturity Path
QA starts with people reading outputs. It ends with reviewer agents auditing reviewer agents - humans auditing the system, coverage compounding while headcount stays flat.
Measured in Production
Confidential — Fintech
Built an AI compliance layer that monitors 100% of loan applications for regulatory violations in real-time, replacing a team of 12 manual reviewers.
100% application coverage vs 20% before
Confidential — Healthcare
Deployed a voice AI triage system that reduced ER wait times by 35% by intelligently routing patients before they see a doctor.
35% reduction in ER wait times
Client name withheld
End-to-end HIPAA-compliant engineering for a US health-tech company building a real-time clinical translation engine - sub-second latency, hallucination detection, and edge-case-language support, all in production.
50,000+ voice minutes of real-time medical translation per month
Client name withheld
End-to-end design and engineering for a US healthcare outreach platform - multi-tenant, multi-language (90+), with AI auto-response, redetermination workflows, and full traceability through Langfuse for every AI decision.
100,000+ AI-generated SMS sent through the platform
How We Build It
Evals without tracing are blind. Tracing without golden data is noise. The layers only work together.
01
Guardrail layers, policy checks, PHI redaction, kill switches, and escalation paths - wired in before launch, not after an incident.
02
Curated with your domain experts, versioned like code, mined from real production failures - the ground truth every change is measured against.
03
Regression suites that gate every model and prompt change. LLM judges calibrated against human ratings, so the scores actually mean something.
04
Groundedness, hallucination rate, refusal correctness, task success - measured per release, then improved deliberately, not vibes-first.
05
Manual review first. Then reviewer agents scoring every output. Then recursive loops where reviewers audit reviewers - and humans audit the system.
06
Every call traced end to end - tokens, latency, cost, tool calls, retrieval hits. When an output looks wrong, you replay it, not guess at it.
Deployed With
LangSmithLangfuseBraintrustArize PhoenixOpenTelemetrypromptfooRagasW&B WeaveThe Team Behind It
100+ full-time product people - engineers, designers, PMs, and QA - led by founders who've built, scaled and exited their own startups. Senior people are on your product from day 1, working your hours. This is the same QA and engineering team running recursive safety loops in production.
Meet the team
Rahul Nair
Co-Founder & Head of Engineering
Architect behind every AI system we ship to production.
+100Full-time team · 0 freelancers · US-hours overlap
Testimonials
Pre-Seed to Series B
“We hired Tequity shortly after closing our pre-seed, and since then they've completely taken over our frontend and DevOps work. Typical turnaround is 1 day for critical bug fixes, 7 days for new features, and 6 weeks for entire MVPs. The software we built together is now used by multiple leading American biopharma companies. I recommend Tequity for any startup from angel round through Series B and beyond.”
Founder & CTO, TerraFlow
“The best outsourced engineering help you can get. Genuinely talented engineers who deliver on time, take full ownership of the product, and push back on your ideas until they understand why you're building each thing.”
Founder, Bantor
4.9/5
Average rating across 100+ customers over 4 years
“They helped us audit our product, identify key UX/UI improvement opportunities, and prioritize quick wins that delivered immediate value. The team has been responsive, collaborative, and consistently delivers high-quality work.”
Founder & CEO, Boxsy
The work behind the words.
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Co-Founder, QuantWheel
“We came in expecting a redesign and got something more useful. Design Labs built us a design system our AI could actually build against, so what we ship stays consistent without us having to think about it. We'd give feedback and see it reflected in the next round, often the same day.”
LET'S TALK
Book a 30-minute call. We'll talk evals, tracing, and what a safety loop looks like for your product.
